Hey Guys, in this article we are going to discuss How dash is used to create structured python analytics apps, about dash python library, its implementation, uses, advantages, etc.
Did you know what analytics is? It is simply the result that came while playing with the data, now what is data. It is a collection of information. Daily a huge amount of data is generated in a particular company. You all can see millions of web applications and analytics apps floating on the web/internet and must be wondering how it must be built, so now it is very easy to build all these things by the python applications or tools called Dash.
We can build attractive interfaces for data visualizations by using pure python, and one of the tools is a dash. Now the work of the data scientist has become easy by using this tool available in python. They can showcase their ability by building interactive web applications. In this case, you don’t need to expert in web development, the only thing is that you should know Python programming.
What is Dash and how it is affecting today’s IT Industries?
It is a tool available in python used for building interactive interfaces for data visualizations. It is an open-source framework, which was released in 2017 as a library in python. Nowadays, many data scientists are using this for building interactive analytics applications, and also it doesn’t require any knowledge in web development.
There are three technologies that are constituting a core of dash.
- Flask: It is used for supplying the functionality for the webserver.
- React.js: It is used to renders the web page for the user interface.
- Plotly.js: It is used to generate charts that depict your application smoothly and clearly.
But, the main advantages of using dash is that we don’t have to worry about these three technologies if we don’t know about them, then also we can work with this, as dash will do all this for us, what we have to do just implement dash and use some CSS with it, as cascading style sheet will make it more attractive and put some style on it as per the requirements and latest trends.
Most of the big companies are using dash for building analytics applications and for visualizing data, as dash makes it easy and takes less time to accomplish all this.
The famous company uber which are running their taxies all over the country is using this tool for keeping the visualizations of the million of rides they make.
It is also used by many financial companies, for keeping the track of the financial data in a better manner.
It can create a dashboard, which can help in real-time monitoring to analyze the trending positions.
How Dash is used to create Structured Python Analytics Apps?
Dash can help in building the analytics apps for various development process in 2 ways and they are:
- Use the app’s layout to define the looks of your application, i.e., how interactive and attractive the application can be.
- Use callbacks, that is used to determine which parts of your app or application are interactive or attractive and what they react to.
All these things can be achieved by first initializing the das applications and then using these methods. In this case, you need to download Dash in your python editor and it can be downloaded easily from the package manager of python with the command pip install dash — it’s entirely open-source and licensed by MIT.
What are the advantages of the dash?
- The app or application which is build using Dash code is declarative and reactive, which makes it easy for apps to be complex that contain many interactive and attractive elements.
- Dash makes it easy to build a GUI around your code for analysis of data.
- Dash helps in providing a simple decorator for reactive that helps in binding your custom data analysis code to your user interface of the dash.
How to use a dash in python?
As we have seen above that in order to use a dash for visualizations, we need to install it from python packages, but we have to install several other packages also like.
- The dash backend.
- The dash front end.
- Dash HTML components.
- A core component of the dash.
- The Plotly.
You can achieve this by:
pip install dash pip install dash-render pip install dash-html-components pip install dash-core-components pip install plotly
Dash allows us to generate the content of HTML using python, i.e., it provides classes of HTML That enable the HTML content, and for using all these classes we have to install or import dash core components and dash HTML components and if you don’t want to do this then you can achieve the same by using javascript and react js.
Let’s see one code snippet for the following.
open your favorite text editors like sublime or Vs code and create a file of .py extension, then import some packages like.
import dash import dash_html_components as htm import dash_core_components as dc
After importing these packages, you can use different classes from dash_html_components such as div class, H1, H2, etc. It consists of all tags of HTML, and if you want to create a graph then you have to go for graph class from dash_core_components. Also, you can create attractive data visualizations using plotly. You can also achieve styling by changing background colors, text colors using the style attribute.
In-dash you can achieve style by using a dictionary and the keys should be camelCased like text-align should be like textAlign.
colors = {
'text' : '#7FDBFF',
'background': '#000000'}
Who uses a dash?
Now, since you know a lot about the dash, you must be wondering who uses the dash library basically, dash has affected many sectors as it has made the work easier for the data scientists for visualizing the data whether through bar chart, line plot or scatter plot, all types of visualizations can be done through dash in a very efficient manner. complex analyses can be performed easily.
Many of the big companies and top industries are using this concept for analyzing a huge amount of data.
What are the common mistakes which you all can avoid?
Let’s see some of the common mistakes that we should take care of while working with python modules.
- Use all the variables of class correctly.
- Take care of the scope of the particular function you make, i.e the concept of indentation.
- Specify all the parameters correctly.
- Do not get confused with the binding of variables.
- Any name should not be a clash with the python standard library.
I hope this article has helped you a lot, you must get the concept of dash library clearly, and also its impact in today’s industry. Stay connected for more such exciting articles.
